%>%                     Pipe
.config                 Reads a configuration file and loads it in the
                        main environment
.stac_bands_select      Select stac items by sits bands.
.stac_items_query       Creates a query to send to STAC api
:=                      Set by reference in data.table
`sits_bands<-`          Replaces the names of the bands
`sits_labels<-`         Change labels of a sits tibble
cerrado_2classes        Samples of classes Cerrado and Pasture
check_functions         Auxiliary check functions
config_show             Shows the contents of the sits configuration
                        file
plot                    Generic interface for ploting time series
plot.classified_image   Generic interface for ploting classified images
plot.keras_model        Generic interface for plotting a Keras model
plot.patterns           Generic interface for ploting patterns
plot.predicted          Generic interface for ploting time series
                        predictions
plot.probs_cube         Generic interface for plotting probability
                        cubes
plot.raster_cube        Generic interface for plotting stack cubes
plot.som_evaluate_cluster
                        Plot information about confusion between
                        clusters
plot.som_map            Generic interface for plotting a SOM map
point_mt_6bands         A time series sample with data from 2000 to
                        2016
samples_modis_4bands    Samples of nine classes for the state of Mato
                        Grosso
samples_mt_6bands       Samples of nine classes for the state of Mato
                        Grosso
sits-package            sits
sits_ResNet             Train a model using the ResNet model
sits_TempCNN            Train a model using the Temporal Convolutional
                        Neural Network
sits_accuracy           Area-weighted classification accuracy
                        assessment
sits_apply              Apply a function over a time series.
sits_bands              Informs the names of the bands
sits_bbox               Get the bounding box of the data
sits_classify           Classify time series or data cube using machine
                        learning models
sits_cluster_clean      Cluster cleaner
sits_cluster_dendro     Clusters a set of time series using
                        aglomerative hierarchical clustering
sits_cluster_frequency
                        Cluster contigency table
sits_create_folds       Create partitions of a data set
sits_cube_copy          Creates the contents of a data cube
sits_data_to_csv        Export a sits tibble data to the CSV format
sits_envelope           Envelope filter
sits_filter             General function for filtering
sits_formula_linear     Define a linear formula for classification
                        models
sits_formula_logref     Define a loglinear formula for classification
                        models
sits_from_zoo           Import time series in the zoo format to a sits
                        tibble
sits_get_data           Obtain time series from different sources
sits_impute_linear      Linear imputation of NA values using C++
                        implementation
sits_interp             Interpolation function of the time series of a
                        sits_tibble
sits_keras_diagnostics
                        Diagnostic information about a Keras deep
                        learning model
sits_kfold_validate     Cross-validate temporal patterns
sits_label_classification
                        Post-process a classified data raster probs to
                        obtain a labelled image
sits_label_majority     Post-process a classified data raster with a
                        majority filter
sits_labels             Returns the information about labels of a data
                        set (tibble or cube)
sits_labels_summary     Returns the information about labels of a
                        tibble data set
sits_lda                Train a sits classification model using linear
                        discriminant analysis
sits_linear_interp      Interpolation function of the time series in a
                        sits tibble
sits_merge              Merge two data sets (time series or cubes)
sits_metadata_to_csv    Export a sits tibble metadata to the CSV format
sits_missing_values     Remove missing values
sits_mlp                Train a deep learning model using multi-layer
                        perceptron
sits_mlr                Train a sits classification model using
                        multinomial log-linear
sits_ndwi               Builds normalized difference water index
sits_patterns           Create temporal patterns using a generalised
                        additive model (gam)
sits_qda                Train a classification model using quadratic
                        discriminant analysis
sits_ranger             Train a sits classifiction model using fast
                        random forest algorithm
sits_regularize         Creates a regularized data cube from an
                        irregular one
sits_rfor               Train a SITS classifiction model using random
                        forest algorithm
sits_sample             Sample a percentage of a time series
sits_savi               Builds soil-adjusted vegetation index
sits_select             Filter bands on a data set (tibble or cube)
sits_sgolay             Smooth the time series using Savitsky-Golay
                        filter
sits_smooth             Post-process a classified data raster probs
                        using smoothing
sits_som_clean_samples
                        Clean samples
sits_som_cluster        Clustering a set of satellite image time series
                        using SOM
sits_som_evaluate_cluster
                        Evaluate cluster
sits_som_map            Generate a Kohonen map for sample quality
                        control
sits_svm                Train a sits classification model using a
                        support vector machine
sits_time_series        Retrieve time series for a row of a sits tibble
sits_timeline           Obtains the timeline
sits_to_xlsx            Saves the results of accuracy assessments as
                        Excel files
sits_to_zoo             Export data to be used to the zoo format
sits_train              Train sits classification models
sits_twdtw_classify     Find matches between patterns and time series
                        using TWDTW
sits_values             Return the values of a given sits tibble as a
                        list of matrices.
sits_view               Generic interface for visualization of data
                        cube
sits_whittaker          Filter the time series using Whittaker smoother
sits_xgboost            Train a model with an extreme gradient boosting
                        machine
timeline_2000_2017      The timeline for the sequence of images for
                        MOD13Q1 collection 6
timeline_2013_2014      The timeline for the sequence of images one
                        year (2013 to 2014)
ts_zoo                  A time series in the ZOO format
